沿海湿地生态系统服务外文文献翻译.docx

沿海湿地生态系统服务外文文献翻译.docx

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沿海湿地生态系统服务外文文献翻译

标题：

沿海湿地生态系统服务

英文

Forecastingecosystemservicestoguidecoastalwetlandrehabilitationdecisions

RyanS.D.Calder,CongjieShi,SaraA.Mason,

LydiaP.Olander,MarkE.Borsuk

Abstract

Coastalwetlandsprovidediverseecosystemservicessuchasfloodprotectionandrecreationalvalue.However,predictingchangesinecosystemservicevaluefromrestorationormanagementischallengingbecauseenvironmentalsystemsarehighlycomplexanduncertain.Furthermore,benefitsarediverseandaccrueovervarioustimescales.WedevelopedageneralizablemathematicalcoastalmanagementmodeltocomparerestorationexpenditurestoecosystemservicebenefitsandapplyittoMcInnisMarsh,MarinCounty,California,USA.Wefindthatbenefitsofrestorationoutweighcostsforawiderangeofassumptions.Forinstance,costsofrestorationrangefrom8–30%oftheincreaseinecosystemservicevalueover50 yearsdependingondiscountrate.Floodprotectionisthedominantmonetizedserviceformostpaybackperiodsanddiscountrates,butotherservices（e.g.,recreation）dominateonshortertimescales（>50%oftotalvalueforpaybackperiods≤4 years）.Wefindthattherangeoftotalecosystemservicevalueisnarrowerthanoverallvariabilityreportedintheliterature,supportingtheuseofmechanisticmethodsindecision-makingaroundcoastalresiliency.However,themagnitudeandrelativeimportanceofecosystemservicesaresensitivetopaybackperiod,discountrateandrisktolerance,demonstratingtheimportanceofprobabilisticdecisionanalysis.Thisworkprovidesamodular,transferrabletooltothatcanalsoinformcoastalresiliencyinvestmentselsewhere.

Keywords：

Ecosystemservices，Economicvaluation，Environmentalmodeling，Coastalwetlands，Climateadaptation，Decisionanalysis

1. Introduction

Coastalwetlandsareincreasinglyrecognizedasmultifunctionalenvironmentsthatprovidediverseservicessuchasfloodprotection,urbanwaterfiltrationandnestingandbreedinghabitatforkeyspecies（Aertsetal.,2014, Costanzaetal.,2008, Yangetal.,2017）.Thehydrologicfunctionofwetlandsisthemostwidelycited,andreclamationanddevelopmentofwetlands（particularlyinfloodplains）havegreatlyincreasedthemagnitudeofflooddamagesintheUnitedStatessincecolonialtimes（AcremanandHolden,2013, HeyandPhilippi,1995）.However,policy-makersandenvironmentalinterestgroupsareincreasinglyviewingwetlandrestorationandconservationastoolstopreserveandenhancediverseecological,recreationalandotherfunctions.Forexample,intheSanFranciscoBayarea,>85%ofhistoricaltidalmarshareahasbeendiked,filledorotherwiselost,endangeringpopulationsofmigratorybirdswhoroostandforagethere（USGS,2018）.Thebenefitstothesekeyspeciesarecommonlycitedjustificationsforwetlandrestorationinitiatives（e.g., SouthBaySaltPondRestorationProject,2015）.Coastalwetlandsthereforeprovidediverseservicestodiversestakeholders,andtheseservicesaccrueindifferentunitsoverdifferenttimescales.This,togetherwiththevariabilityanduncertaintyinherentinenvironmentalsystems,presentsachallengetodecision-makerswhomustweightheseprospectivefuturebenefitsagainstcostsofrestorationorpreservation.

Thereexistmultipleframeworkstocalculateecologicalvalueofland-usescenarios,buttheirutilityindecision-makinghasbeenlimitedbynarrowscopeandpoorsupportforprospectiveanalysis. Grêt-Regameyetal.（2017） identify68uniqueecosystemservicevaluationtools,ofwhichthemostcomprehensiveandwidelycitedisthe IntegratedValuationofEcosystemServicesandTradeoffs （InVEST）model（Sharpetal.,2018）.Thesetoolscouplebiophysicalandeconomicmodelsandcancontributetothepolicyprocessbyestimatingbenefitsassociatedwithalternativeland-useassumptions（Goldsteinetal.,2012）.However,existingtoolstendtofocusonasmallsubsetofecosystemservices（deGrootetal.,2010, Grêt-Regameyetal.,2017）andmostlydonotcharacterizethelargeparameterspacecharacteristicofunknown,alternativestatesofcomplexenvironmentalsystems（HamelandBryant,2017）.Conversely,widevariabilityinretrospectiveecosystemservicevaluationshaslimitedtheutilityoflandcover-basedbenefits-transferapproaches.Forexample,inthecaseofwetlands,totalecosystemservicevaluemayrangefrom<2$ha−1 yr−1 to>340000$ha−1 yr−1 （2017-$）,dependingonhighlysite-specificfactorssuchasthevalueofavoidedfloodsandthepotentialforconservationofvulnerablespecies（Branderetal.,2006）.Overall,ithasbeenpoorlyunderstoodwhetherprospectiveecosystemservicemodelscannarrowtheseuncertainties,andthishaslimitedtheinterpretabilityofmodeloutputsbydecision-makers（HamelandBryant,2017）.

Ourpreviousworkhasdemonstratedthatcontrollingforuncertaintiesthatarecorrelatedacrosspolicyalternativescansubstantiallyincreaseconfidenceinvaluationsofproposedinterventions（ReichertandBorsuk,2005）.Isolatinguncertaintiesassociatedwithhypotheticalenvironmentalchangesfromthebaselineuncertaintiesinherenttoenvironmentalsystemshoweverrequiresthatanalysisbecarriedoutwithinintegratedprobabilisticenvironmentsor“wrappers”,afacilitynotsupportedbycommonlyusedoff-the-shelfecosystemservicevaluationtools（HamelandBryant,2017）.Indeed,availabletoolstendtomakeuncertaintyanalysisatime-consumingprocess,anditisfrequentlyneglectedinpractice:

 Seppeltetal.（2011） foundthatonlyonethirdof460studiescarriedoutevenbasicuncertaintyanalysis.Emerginggraphicalmethodsknownvariouslyas“resultschains”（Tallisetal.,2017）,“logicmodels”（CDC,2010）and“Bayesiannetworks”（Pearl,1995）arewell-suitedtofacilitatequantitativemodelingthattrackscorrelationsofuncertainvariables.Previously,wehavedemonstratedhowthesetechniquescanbeusedtoencodeinteractingbiophysicalpathwaysbetweenenvironmentalpolicydecisionsandecosystemservicesofrelevancetostakeholdersintermsofavailabledataandmodelingcapacity（Borsuketal.,2001, Borsuketal.,2012, MasonandOlander,2018）.

Recentupdatestofederalguidelinesforenvironmentalprojects,riskmanagement,andnaturalresourcemanagementrequireexplicitcharacterizationofecosystemservicevalueofpolicyalternatives（CouncilonEnvironmentalQuality（CEQ）,2014, FederalEmergencyManagementAgency（FEMA）,2016, Olanderetal.,2018, UnitedStatesForestService,2012）.Therefore,methodstoimproveforecastingandbenefitsmodelingareurgentlyneeded.Managementofcoastalwetlandspresentsaparticularlyimportantresearchareagiventheincreasingattentiontheseenvironmentsarereceivinginternationally（Barbier,2013, Yangetal.,2017）andthepoorlycharacterizedconceptualgapsbetweenbiophysicalconditionsandsociallyvaluedoutcomes（Boydetal.,2015）.WeproposethatstructuringenvironmentalpolicyquestionswithinaBayesiananalyticalgraphicalmodelingframeworkhasthepotentialtoimprovedecision-makingbynarrowingandrobustlyassessinguncertainties.Inparticular,methodsthattrackcorrelateduncertaintiesmayprovideamorerobustquantificationofbenefitsofpolicyalternativesinhighlycomplexandvariableenvironmentssuchascoastalwetlands.

Here,wesynthesizecurrentscientificunderstandingofthebiophysicalpathwaysbetweencoastalrestorationandecosystemserviceendpointsintoaquantitative,probabilisticmodel.UsingacasestudyfromtheSanFranciscoBayarea,California,USA,weevaluatehowrisktoleranceanddiscountrateinteractwithmodeluncertaintiesandnon-stationaritiestodeterminepolicyoptima.ThisworkcanbeeasilytransferredtoothersitesintheSanFranciscoBayestuary,whereecosystemservicesarelikelytobesimilarandwherewetlandrestorationandconservationhavebecomeenvironmentalmanagementpriorities（USGS,2018）.Morebroadly,thisworkevaluateshowmechanisticallyexplicitmodelscaninformdecisionsinthehighlycomplexanduncertainsettingofcoastalwetlands.Finally,wearguethatpolicyinterpretabilityofbiophysicalandeconomicmodeloutputisdependentonconsiderationofdecision-analyticparameterssuchasdiscountrate,paybackperiodandrisktolerance.Thispointstotheimportanceofstructuringsuchanalysiswithinprobabilistic,decision-analyticenvironments.

2. Methods

Wepresentadecisionanalyticframeworktoreconcileuncertainfuturecostsandecosystemservicebenefitsassociatedwithalternativemanagementdecisionsforcoastalmarshenvironments.Tocapturetheuncertaintiesinmodelformulations,wenestbiophysicalandeconomicmodelswithinaprobabilisticMonteCarloframework.Inpreviouswork,wedevelopedgeneralandsite-specificconceptualmodelsforecosystemserviceimpactsofcoastalmanagementinterventions（Section2.1）.Here,weextendthesite-specificconceptualmodeldevelopedfortheMcInnisMarshrestorationproject,MarinCounty,California,USA（Section2.2）,byreplacingconceptualrelationshipswithquantitativebiophysicalandeconomicmodels.

Ourintegrativeframeworkallowsmanagementscenariostobecomparedintermsofprobabilisticallydistributedfuturecostsandbenefitscorrespondingto

（1）waterqualityimprovements;

（2）reducedrain-drivenflooding;（3）improvedrecreationalvalue;（4）enhancedspeciesabundance;and（5）carbonsequestration,incomparisonwithrecurringandupfrontmanagementcosts（e.g.,creekdredging）.Wequantifytheimpactofdecision-makerpreferencesandvalues（paybackperiod,discountrateandrisktolerance）oneconomicvaluationsandexploretherolethesemayhaveindecision-making.

2.1. Conceptualmodeldevelopment

Inpreviouswork,wedevelopedaconceptualmod